Engineer II at Arthrex developing and improving manufacturing processes for Class I, II, and III medical devices in a collaborative team environment.
About the role
- Junior Engineer creating GCP data-driven solutions for enterprise data architecture. Collaborating with stakeholders on data needs and optimizing performance and reliability.
Responsibilities
- Responsibilities **• Design and build GCP data driven solutions for enterprise data warehouse and data lakes **• Design and implement scalable data architectures on GCP, including data lakes, warehouses, and real-time processing systems.**• Utilize ML Services like Vertex AI.**• Develop and optimize ETL/ELT pipelines using tools like Python, SQL, and streaming technologies (e.g., Kafka, Apache Airflow).**• Architect Historical and Incremental Loads and Refine Architecture on an ongoing basis**• Manage and optimize data storage, partitioning, and clustering strategies for high performance and reliability, utilizing services such as BigQuery, Spark, Pub/Sub, and Object Storage.**• Collaborate with data scientists, Data engineers, and other stakeholders to understand data needs and deliver solutions aligned with business objectives, security, and data governance.**• Automate infrastructure and deployments using Infrastructure as Code (IaC) using tools like Terraform and CI/CD practices (e.g., Tekton) to ensure reliability and scalability.**• Operationalize machine learning models by building data infrastructure and managing structured and unstructured data, supporting AI/ML/LLM workflows, including data labeling, classification, and document parsing.**• Monitor and troubleshoot data pipelines and systems to identify and resolve issues related to performance, reliability, and cost-effectiveness.**• Document data processes, pipeline designs, and architecture, contributing to knowledge transfer and system maintenance.**
Requirements
- **Qualifications and Skills **
- Must have -
- Professional GCP - Data Engineer Certification.
- 2 + years coding skills in Java/Python and Terraform.
- 2+ years’ experience
- Experience in working with Agile and Lean methodologies.
- GCP Expertise: Strong proficiency in GCP services, including BigQuery, Dataflow, Dataproc, Data Fusion, Air Flow, Pub/Sub, Cloud Storage, Vertex AI, Cloud Functions, and Cloud Composer, GCP based Big Data deployments (Batch/Real-Time) leveraging Big Query, Big Table
- Programming & Scripting: Expert-level skills in Python and SQL are essential. Familiarity with languages like Scala or Java can also be beneficial, especially for working with tools like Apache Spark.
- Data Engineering Fundamentals: Solid understanding of data modeling, data warehousing concepts, ETL/ELT processes, and big data architecture, Designing pipelines and architectures for data processing.
- Big Data Technologies: Experience with technologies like Apache Spark, Apache Beam, and Kafka is often required.
- DevOps & MLOps: Knowledge of DevOps methodologies, CI/CD pipelines, and MLOps practices, including integrating data pipelines with ML workflows.
- Security & Compliance: Expertise in implementing Identity and Access Management (IAM) policies, ensuring data encryption, and adhering to data privacy regulations.
- Analytical & Problem-Solving Skills: Demonstrated ability to analyze complex datasets, identify trends, debug issues, and optimize systems for performance and cost efficiency.
- Communication & Collaboration: Excellent communication and teamwork skills, with the ability to collaborate effectively with technical and non-technical stakeholders in agile environments.
- Experienced in Visualization Tool – Qlik, Looker Studio, Power BI
- Knowledge of VBA, will be a plus
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